%0 Journal Article %1 noauthororeditor %A Kharya, Shweta %D 2012 %J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) %K Association Bayesian Breast Classification Data Diagnosis Mining Naive.BayesC4.5 Network Networks Neural Prognosis Rule algorithm cancer decision tree %N 2 %P 55-66 %R 10.5121/ijcseit.2012.2206 %T USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASE %U http://airccse.org/journal/ijcseit/papers/2212ijcseit06.pdf %V 2 %X Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years. In this paper we have discussed various data mining approaches that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is to recur in patients that have had their cancers excised. This study paper summarizes various review and technical articles on breast cancer diagnosis and prognosis also we focus on current research being carried out using the data mining techniques to enhance the breast cancer diagnosis and prognosis.

@article{noauthororeditor, abstract = {Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years. In this paper we have discussed various data mining approaches that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is to recur in patients that have had their cancers excised. This study paper summarizes various review and technical articles on breast cancer diagnosis and prognosis also we focus on current research being carried out using the data mining techniques to enhance the breast cancer diagnosis and prognosis. }, added-at = {2018-06-22T07:54:23.000+0200}, author = {Kharya, Shweta}, biburl = {https://www.bibsonomy.org/bibtex/2b1a500d6c33277b3dccfa26f5786c588/ijcseit}, doi = {10.5121/ijcseit.2012.2206}, interhash = {e36ace1d332e3c9e4bf7160d0ae6d358}, intrahash = {b1a500d6c33277b3dccfa26f5786c588}, issn = {2231-3117 [Online] ; 2231-3605 [Print]}, journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)}, keywords = {Association Bayesian Breast Classification Data Diagnosis Mining Naive.BayesC4.5 Network Networks Neural Prognosis Rule algorithm cancer decision tree}, language = {English}, month = apr, number = 2, pages = {55-66}, timestamp = {2018-06-22T07:54:23.000+0200}, title = {USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASE}, url = {http://airccse.org/journal/ijcseit/papers/2212ijcseit06.pdf}, volume = 2, year = 2012 }